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Chocolate model with all coefficients random

Now that we have the effects coding stored with the chocolate data, we are ready to fit a model where all the coefficients are normally distributed. In order to do that, we need to create the rpar vector to input to mlogit(). That's a bit tricky, so I've written the code for you, but you should run it to see how it works. Then, you are going to write the call to mlogit().

Bu egzersiz, kursun bir parçasıdır

Choice Modeling for Marketing in R

Kursa Göz Atın

Egzersiz talimatları

  • The first two inputs are the model formula Selection ~ 0 + Brand + Type + Price and the data chocolate.
  • The next input should be rpar = my_rpar which tells mlogit() which coefficients we want to be normally distributed.
  • The last input should be panel = TRUE.

Uygulamalı etkileşimli egzersiz

Bu egzersizi bu örnek kodu tamamlayarak deneyin.

# create my_rpar vector
choc_m2 <- mlogit(Selection ~ 0 + Brand + Type + Price, data=chocolate)
my_rpar <- rep("n", length(choc_m2$coef))
names(my_rpar) <- names(choc_m2$coef)
my_rpar

# fit model with random coefficients
choc_m7 <- mlogit(___)
Kodu Düzenle ve Çalıştır